Pitney Bowes (PBI) EPS (Diluted) (2009 - 2026)
Pitney Bowes (PBI) reported EPS (Diluted) of $0.36 for Q2 2026, up 116.7% from $0.17 a year earlier but down 8.8% from the prior quarter.
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Analysis
Pitney Bowes (PBI) EPS (Diluted) (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Pitney Bowes' EPS (Diluted) came in at $1.35; for FY2025, it came in at $0.84.
- By year, EPS (Diluted) came in at -$1.12 in FY2024, -$2.20 in FY2023, $0.21 in FY2022 and -$0.01 in FY2021.
- Five-year quarterly EPS (Diluted) spans a low of -$1.27 in Q4 2023 and a high of $0.39 in Q1 2026.
- Per Business Quant data, the three quarters before Q2 2026 came in at $0.39 (Q1 2026), $0.16 (Q4 2025) and $0.31 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EPS (Diluted) (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 122.50 Bn | 82.91 Bn | 6.13 Bn | 3.80 |
| 2 | Cintas | 78.05 Bn | 77.24 Bn | 1.48 Bn | 1.26 |
| 3 | Iron Mountain | 33.02 Bn | 32.53 Bn | 1.07 Bn | 0.34 |
| 4 | APi | 16.68 Bn | 13.72 Bn | 703.00 Mn | 0.20 |
| 5 | Rollins | 14.49 Bn | 14.04 Bn | 569.95 Mn | 0.30 |
| 6 | Aramark | 14.11 Bn | 12.13 Bn | 430.34 Mn | 0.36 |
| 7 | UL Solutions | 13.27 Bn | 12.05 Bn | 417.00 Mn | 1.21 |
| 8 | Gartner | 11.78 Bn | 5.47 Bn | 1.19 Bn | 4.14 |
| 9 | Rentokil Initial | 9.98 Bn | 3.32 Bn | - | - |
| 10 | Pitney Bowes | 2.24 Bn | 1.01 Bn | 254.70 Mn | 0.36 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 0.36 |
| Mar 31, 2026 | 0.39 |
| Dec 31, 2025 | 0.16 |
| Sep 30, 2025 | 0.31 |
| Jun 30, 2025 | 0.17 |
| Mar 31, 2025 | 0.19 |
| Dec 31, 2024 | -0.20 |
| Sep 30, 2024 | -0.75 |
| Jun 30, 2024 | -0.14 |
| Mar 31, 2024 | -0.02 |
| Dec 31, 2023 | -1.27 |
| Sep 30, 2023 | -0.07 |
| Jun 30, 2023 | -0.81 |
| Mar 31, 2023 | -0.04 |
| Dec 31, 2022 | 0.04 |
| Sep 30, 2022 | 0.03 |
| Jun 30, 2022 | 0.02 |
| Mar 31, 2022 | 0.12 |
| Dec 31, 2021 | 0.01 |
| Sep 30, 2021 | 0.05 |
API Access
Pitney Bowes EPS (Diluted) API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=eps-diluted&ticker=PBI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "eps-diluted", "ticker": "PBI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=eps-diluted&ticker=PBI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();